AI Agent Model Router / Fallback Cost Calculator
Compare the cost and reliability of routing AI agent requests across multiple LLM providers with fallback logic, cache hits, and retry penalties.
Routing scenario preset
Traffic & routing
Provider mix under this strategy
| Provider | Primary % | Fallback % | Effective $/1M tokens | Est. monthly cost |
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Base monthly cost
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Fallback premium
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Retry penalty
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Total routed cost
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Cost vs single-provider alternatives
| Provider | Single-provider cost | vs routed cost | Reliability |
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Verdict
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Frequently asked questions
What is an AI agent model router?
A model router sends each agent request to the best LLM provider based on cost, quality, latency, or reliability rules. If the primary provider fails or is rate-limited, the router falls back to a secondary provider so the agent stays available.
How does fallback rate affect monthly cost?
Fallback requests usually land on a more expensive or higher-quality model. The calculator adds that premium to your effective per-request cost and shows how much extra you pay for resilience.
What is cached-input ratio?
It is the share of input tokens that your provider can serve from a prompt cache at a discounted rate. Higher ratios reduce cost significantly for agents with long repeated system prompts.
Which routing strategy should I start with?
Most agents should start with Balanced Cost + Quality. It keeps cost reasonable while reserving premium models for complex tasks. Switch to Cheapest First only if failure impact is low and volume is very high.
Do retries really add cost?
Yes. Each retry consumes tokens again. The calculator applies a retry penalty equal to the expected extra calls multiplied by the average cost of the fallback provider.
Prices are per 1M tokens in USD. Check provider sites for current rates.